U.S. Airline Pilot Retention Analysis

General Factor Rankings and Subfactor Priorities

Authors

Affiliations

Michael J. Hickey

University of North Dakota

Marina Efthymiou

Dublin City University

James Higgins

University of North Dakota

Aman Gupta

Embry-Riddle Aeronautical University

Robert Walton

Embry-Riddle Aeronautical University

1 Overview

Repository: https://github.com/mikehickey2/US-Airline-Pilot-Retention-Analysis

This analysis examines pilot retention priorities from a survey of U.S. airline pilots (n = 76). The analysis has two parts:

1. General Retention Factors - Rankings of six broad retention constructs and demographic comparisons
2. Subfactor Analysis - Within-construct priorities for 31 specific retention elements

Figure 1: Factors of Pilot Retention in U.S. Airlines

2 Statistical Methods

2.1 Sample and Data Collection

Survey data was collected from U.S. airline pilots in May 2025. After exclusions for incomplete responses and non-air carrier pilots, n = 76 valid responses remained for analysis.

2.2 Statistical Tests

All ranking data is ordinal; therefore, non-parametric tests are used throughout:

• Friedman Test: Within-subjects comparison of factor rankings
• Mann-Whitney U: Between-groups comparison for binary demographics
• Kruskal-Wallis H: Between-groups comparison for multi-level demographics

2.3 Multiple Testing Correction

This quantitative study employs a hierarchical false discovery rate (FDR) control procedure:

General Factor Analysis (30 tests): Benjamini-Hochberg FDR at q = 0.10 applied across all demographic comparisons.

Subfactor Analysis (155 tests): Two-step hierarchical procedure:

1. Screening: For each construct, compute minimum p-value across demographics. Apply BH-FDR at q = 0.10 to these 6 screening p-values.
2. Within-construct testing: For constructs passing screening, apply Holm’s procedure at alpha = 0.05 to demographic comparisons.

Rationale: Standard Bonferroni correction (alpha/155 = 0.0003) is overly conservative for exploratory research, causing 50-70% Type II error rates. FDR control at q = 0.10 balances discovery against false positives appropriately for hypothesis generation.

2.4 Effect Sizes

• Mann-Whitney U: Rank-biserial correlation r (small < .3, medium .3-.5, large > .5)
• Kruskal-Wallis: Eta-squared (small < .01, medium .01-.06, large > .06)

2.5 Software

Analysis conducted in R 4.5.1 using: tidyverse, rstatix, coin, DescTools, knitr, janitor.

Code Availability: The complete analysis code is available at scripts/analysis/unified_retention_analysis.qmd in the GitHub repository: https://github.com/mikehickey2/US-Airline-Pilot-Retention-Analysis

3 Setup

4 Data Loading and Preprocessing

Data Exclusion Summary

exclusion_reason	n
did_not_finish	35
included	76
not_air_carrier	2

Table 1: Sample Demographic Summary

Demographic	Category	n
Age Group	≤ 35 years	58
	> 35 years	18
Experience	Q1 (least)	19
	Q2	19
	Q3	19
	Q4 (most)	19
Gender	Male	67
	Female	8
	Other/NA	1
Military Background	Yes	7
	No	69
Position	Captain	26
	First Officer	50
Carrier Type	Regional	57
	Major	11
	LCC	5
	Other	3

Final sample: 76 pilots included in analysis.

5 Part 1: General Retention Factor Analysis

This section analyzes the rankings of six broad retention constructs:

1. Financial (salary, benefits, bonuses)
2. Quality of Life/Lifestyle (schedule, family, work-life balance)
3. Professional Opportunity (stability, upgrade, aircraft type)
4. Recognition (uniform, respect, awards)
5. Schedule (fixed vs variable, bidding systems)
6. Operational (SOPs, training, equipment, pilot skill)

5.1 Descriptive Statistics

Table 1: Rank Summary for General Retention Factors

factor	n	median	iqr	mean	sd
financial	76	2	2	2.22	1.10
lifestyle	76	2	2	1.99	1.16
schedule	76	2	1	2.46	1.01
operational	76	4	1	4.41	1.07
professional	76	5	1	4.37	1.16
recognition	76	6	1	5.55	0.84

Table 2: Number (and %) of Pilots Ranking Each Factor #1

factor	n	percent
lifestyle	34	44.7
financial	25	32.9
schedule	13	17.1
professional	3	3.9
operational	1	1.3

5.2 Friedman Test: Overall Factor Rankings

Friedman Test: Overall Difference in Factor Rankings

.y.	n	statistic	df	p	method
rank	76	234.316	5	0	Friedman test

Table 3: Pairwise Wilcoxon Tests Between General Factors (Holm-adjusted)

comparison	statistic	p	p.adj	sig
financial vs lifestyle	1700.5	0.209	0.426
financial vs operational	206.5	0.000	0.000	*
financial vs professional	173.0	0.000	0.000	*
financial vs recognition	10.5	0.000	0.000	*
financial vs schedule	1187.0	0.142	0.426
lifestyle vs operational	104.0	0.000	0.000	*
lifestyle vs professional	149.5	0.000	0.000	*
lifestyle vs recognition	45.0	0.000	0.000	*
lifestyle vs schedule	1009.0	0.016	0.062
operational vs professional	1437.0	0.892	0.892
operational vs recognition	477.0	0.000	0.000	*
operational vs schedule	2793.0	0.000	0.000	*
professional vs recognition	427.0	0.000	0.000	*
professional vs schedule	2667.0	0.000	0.000	*
recognition vs schedule	2905.5	0.000	0.000	*

5.3 Demographic Comparisons

5.3.1 Age Groups (≤35 vs >35)

Table 4: Mann-Whitney U Tests - Age Groups (≤35 vs >35)

factor	> 35_n	≤ 35_n	> 35_median	≤ 35_median	statistic	p_raw	p_adj_fdr	sig_fdr10	n1	n2
lifestyle	18	58	2.5	1	726.0	0.008	0.049	*	18	58
financial	18	58	2.0	2	436.0	0.276	0.736		18	58
schedule	18	58	2.0	2	466.0	0.477	0.736		18	58
professional	18	58	4.0	5	479.0	0.584	0.736		18	58
recognition	18	58	6.0	6	488.5	0.613	0.736		18	58
operational	18	58	4.0	4	505.0	0.832	0.832		18	58

5.3.2 Experience Quartiles

Table 5: Median Rank of General Factors by Experience Quartile

factor	Q1 (least)_n	Q2_n	Q3_n	Q4 (most)_n	Q1 (least)_median	Q2_median	Q3_median	Q4 (most)_median
financial	19	19	19	19	2	2	2	2
lifestyle	19	19	19	19	1	2	2	2
operational	19	19	19	19	5	4	4	4
professional	19	19	19	19	4	5	5	5
recognition	19	19	19	19	6	6	6	6
schedule	19	19	19	19	3	2	2	2

Table 6: Kruskal-Wallis Tests for Experience Quartiles (FDR-adjusted)

factor	statistic	df	p_raw	p_adj_fdr	sig_fdr10
financial	0.551	3	0.908	0.908
lifestyle	3.854	3	0.278	0.834
operational	1.364	3	0.714	0.908
professional	1.015	3	0.798	0.908
recognition	4.639	3	0.200	0.834
schedule	2.619	3	0.454	0.908

5.3.3 Gender (Male vs Female)

Table 7: Median Rank of General Factors by Gender

factor	Female_n	Male_n	Female_median	Male_median
financial	8	67	3	2
lifestyle	8	67	1	2
operational	8	67	4	5
professional	8	67	5	5
recognition	8	67	6	6
schedule	8	67	2	2

Table 8: Mann-Whitney U Tests - Male vs Female (Exact test, FDR-adjusted)

factor	statistic	p_raw	p_adj_fdr	sig_fdr10	n1	n2
financial	365	0.084	0.168		8	67
lifestyle	212	0.312	0.353		8	67
operational	157	0.047	0.168		8	67
professional	320	0.353	0.353		8	67
recognition	356	0.061	0.168		8	67
schedule	192	0.174	0.261		8	67

Note

Note on Gender Comparisons: With only 8 female respondents, statistical power for detecting gender differences is limited. Results should be interpreted cautiously.

5.3.4 Military Background

Table 9: Median Rank of General Factors by Military Background

factor	No_n	Yes_n	No_median	Yes_median
financial	69	7	2	2
lifestyle	69	7	2	2
operational	69	7	4	5
professional	69	7	5	4
recognition	69	7	6	6
schedule	69	7	2	2

Table 10: Mann-Whitney U Tests - Military vs Civilian (FDR-adjusted)

factor	statistic	p_raw	p_adj_fdr	sig_fdr10	n1	n2
financial	220.5	0.701	0.841		69	7
lifestyle	251.5	0.856	0.856		69	7
operational	211.5	0.578	0.841		69	7
professional	277.5	0.502	0.841		69	7
recognition	198.5	0.338	0.841		69	7
schedule	284.5	0.423	0.841		69	7

5.3.5 Flight-Deck Position (Captain vs First Officer)

Table 11: Median Rank of General Factors by Flight-Deck Position

factor	Captain_n	First Officer_n	Captain_median	First Officer_median
financial	26	50	2	2
lifestyle	26	50	2	2
operational	26	50	5	4
professional	26	50	4	5
recognition	26	50	6	6
schedule	26	50	2	2

Table 12: Mann-Whitney U Tests - Captain vs First Officer (FDR-adjusted)

factor	statistic	p_raw	p_adj_fdr	sig_fdr10	n1	n2
financial	489.0	0.067	0.200		26	50
lifestyle	723.0	0.398	0.478		26	50
operational	865.0	0.014	0.082	*	26	50
professional	543.0	0.219	0.438		26	50
recognition	573.5	0.296	0.444		26	50
schedule	669.0	0.832	0.832		26	50

5.3.6 Carrier Type

Table 13: Median Rank of General Factors by Carrier Type

factor	LCC_n	Major_n	Other_n	Regional_n	LCC_median	Major_median	Other_median	Regional_median
financial	5	11	3	57	3	2	1	2
lifestyle	5	11	3	57	2	1	2	2
operational	5	11	3	57	4	4	4	4
professional	5	11	3	57	5	5	4	5
recognition	5	11	3	57	6	6	6	6
schedule	5	11	3	57	1	3	3	2

Table 14: Kruskal-Wallis Tests Across Carrier Types (FDR-adjusted)

factor	statistic	df	p_raw	p_adj_fdr	sig_fdr10
financial	5.451	3	0.142	0.426
lifestyle	1.479	3	0.687	0.687
operational	2.792	3	0.425	0.661
professional	2.304	3	0.512	0.661
recognition	2.102	3	0.551	0.661
schedule	9.233	3	0.026	0.158

5.4 Summary: General Factor Results

Summary: General Factor Demographic Comparisons (BH-FDR at q=0.10)

Demographic	Tests	Min_p_raw	Min_p_adj	Significant_q10
Age (≤35 vs >35)	6	0.0081	0.0488	1
Experience Quartiles	6	0.2000	0.8340	0
Gender (Male vs Female)	6	0.0466	0.1680	0
Military Background	6	0.3380	0.8412	0
Flight-Deck Position	6	0.0136	0.0816	1
Carrier Type	6	0.0264	0.1584	0

General Factor Analysis Summary:

• Total demographic comparisons: 36
• Significant at FDR q=0.10: 2
• Discovery rate: 5.6%

6 Part 2: Subfactor Analysis

This section examines the 31 subfactors within each retention construct and tests for demographic differences in within-construct priorities.

6.1 Financial Subfactors

Financial Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Competitive salary	76	2.0	1.64	0.74	47.37
Allowances and soft pay	76	4.0	3.96	1.24	1.32
Benefits package	76	3.0	3.36	1.14	5.26
Disability insurance	76	4.5	4.41	1.05	1.32
Job security	76	2.0	2.09	1.28	44.74
New hire/longevity bonuses	76	6.0	5.54	0.92	0.00

Financial: Friedman Test

.y.	n	statistic	df	p	method
rank	76	231.06	5	0	Friedman test

Financial: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Competitive salary	460.5	0.406	1.000	ns	0.096	small
Allowances and soft pay	502.0	0.806	1.000	ns	0.029	small
Benefits package	583.0	0.444	1.000	ns	0.088	small
Disability insurance	515.0	0.934	1.000	ns	0.010	small
Job security	516.5	0.948	1.000	ns	0.008	small
New hire/longevity bonuses	619.0	0.127	0.762	ns	0.176	small

Financial: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Competitive salary	363.0	0.069	0.415	ns	0.211	small
Allowances and soft pay	332.5	0.258	1.000	ns	0.132	small
Benefits package	204.0	0.259	1.000	ns	0.131	small
Disability insurance	174.0	0.093	0.464	ns	0.195	small
Job security	205.0	0.255	1.000	ns	0.133	small
New hire/longevity bonuses	311.0	0.339	1.000	ns	0.112	small

Financial: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Competitive salary	603.5	0.574	1.000	ns	0.065	small
Allowances and soft pay	596.0	0.547	1.000	ns	0.070	small
Benefits package	646.5	0.973	1.000	ns	0.005	small
Disability insurance	730.0	0.362	1.000	ns	0.105	small
Job security	674.5	0.781	1.000	ns	0.033	small
New hire/longevity bonuses	755.5	0.137	0.822	ns	0.171	small

Financial: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Competitive salary	311.5	0.164	0.984	ns	0.161	small
Allowances and soft pay	233.5	0.890	1.000	ns	0.017	small
Benefits package	264.5	0.676	1.000	ns	0.049	small
Disability insurance	229.0	0.821	1.000	ns	0.027	small
Job security	169.5	0.173	0.984	ns	0.157	small
New hire/longevity bonuses	246.0	0.926	1.000	ns	0.012	small

Financial: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Competitive salary	1.885	3	0.597	1	ns	-0.015	small
Allowances and soft pay	3.862	3	0.277	1	ns	0.012	small
Benefits package	3.708	3	0.295	1	ns	0.010	small
Disability insurance	4.724	3	0.193	1	ns	0.024	small
Job security	2.263	3	0.520	1	ns	-0.010	small
New hire/longevity bonuses	4.884	3	0.181	1	ns	0.026	small

6.2 Quality of Life Subfactors

Quality of Life Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Predictable schedule	76	2	2.51	1.13	19.74
Vacation time	76	4	4.12	1.18	1.32
Family-friendly policies	76	5	4.53	1.28	1.32
Possibility of being based at home	76	2	2.70	1.87	39.47
Travel benefits	76	5	4.87	1.20	1.32
Work-life balance	76	2	2.28	1.41	36.84

Quality of Life: Friedman Test

.y.	n	statistic	df	p	method
rank	76	139.489	5	0	Friedman test

Quality of Life: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Predictable schedule	329.5	0.015	0.088	ns	0.281	small
Vacation time	544.5	0.780	1.000	ns	0.033	small
Family-friendly policies	481.0	0.610	1.000	ns	0.059	small
Possibility of being based at home	529.5	0.929	1.000	ns	0.011	small
Travel benefits	570.0	0.543	1.000	ns	0.071	small
Work-life balance	640.0	0.134	0.670	ns	0.173	small

Quality of Life: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Predictable schedule	197.5	0.212	1.000	ns	0.145	small
Vacation time	253.5	0.803	1.000	ns	0.030	small
Family-friendly policies	265.5	0.972	1.000	ns	0.005	small
Possibility of being based at home	259.0	0.880	1.000	ns	0.019	small
Travel benefits	359.5	0.102	0.612	ns	0.190	small
Work-life balance	290.5	0.693	1.000	ns	0.047	small

Quality of Life: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Predictable schedule	722.0	0.415	1	ns	0.094	small
Vacation time	604.0	0.605	1	ns	0.060	small
Family-friendly policies	739.5	0.315	1	ns	0.116	small
Possibility of being based at home	556.0	0.287	1	ns	0.123	small
Travel benefits	576.5	0.402	1	ns	0.097	small
Work-life balance	711.5	0.485	1	ns	0.081	small

Quality of Life: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Predictable schedule	193.5	0.375	1.000	ns	0.103	small
Vacation time	216.0	0.641	1.000	ns	0.055	small
Family-friendly policies	200.5	0.453	1.000	ns	0.087	small
Possibility of being based at home	357.5	0.031	0.186	ns	0.249	small
Travel benefits	236.5	0.932	1.000	ns	0.011	small
Work-life balance	198.0	0.420	1.000	ns	0.094	small

Quality of Life: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Predictable schedule	7.452	3	0.059	0.353	ns	0.062	moderate
Vacation time	5.189	3	0.158	0.790	ns	0.030	small
Family-friendly policies	4.905	3	0.179	0.790	ns	0.026	small
Possibility of being based at home	2.634	3	0.451	1.000	ns	-0.005	small
Travel benefits	1.214	3	0.750	1.000	ns	-0.025	small
Work-life balance	1.712	3	0.634	1.000	ns	-0.018	small

6.3 Professional Opportunity Subfactors

Professional Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Financially stable airline	76	1	1.18	0.42	82.89
Opportunity for rapid upgrade	76	3	3.45	1.09	1.32
Opportunity to fly larger aircraft	76	3	3.26	1.43	10.53
Promotion/upgrade based on merit	76	3	3.45	1.24	5.26
Upgrade based on length of service	76	4	3.66	0.97	0.00

Professional: Friedman Test

.y.	n	statistic	df	p	method
rank	76	127.663	4	0	Friedman test

Professional: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Financially stable airline	442.5	0.139	0.695	ns	0.171	small
Opportunity for rapid upgrade	560.0	0.636	1.000	ns	0.055	small
Opportunity to fly larger aircraft	558.5	0.650	1.000	ns	0.053	small
Promotion/upgrade based on merit	495.0	0.739	1.000	ns	0.039	small
Upgrade based on length of service	498.5	0.769	1.000	ns	0.034	small

Professional: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Financially stable airline	253.0	0.705	1.000	ns	0.045	small
Opportunity for rapid upgrade	316.5	0.394	1.000	ns	0.099	small
Opportunity to fly larger aircraft	355.5	0.123	0.492	ns	0.179	small
Promotion/upgrade based on merit	173.5	0.097	0.484	ns	0.193	small
Upgrade based on length of service	216.5	0.360	1.000	ns	0.107	small

Professional: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Financially stable airline	593.5	0.348	1	ns	0.109	small
Opportunity for rapid upgrade	696.5	0.603	1	ns	0.060	small
Opportunity to fly larger aircraft	679.5	0.743	1	ns	0.038	small
Promotion/upgrade based on merit	645.0	0.960	1	ns	0.006	small
Upgrade based on length of service	578.0	0.414	1	ns	0.094	small

Professional: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Financially stable airline	287.0	0.216	0.648	ns	0.144	small
Opportunity for rapid upgrade	323.5	0.130	0.520	ns	0.175	small
Opportunity to fly larger aircraft	135.0	0.049	0.246	ns	0.227	small
Promotion/upgrade based on merit	229.0	0.824	0.824	ns	0.027	small
Upgrade based on length of service	303.0	0.253	0.648	ns	0.132	small

Professional: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Financially stable airline	1.667	3	0.644	1.000	ns	-0.019	small
Opportunity for rapid upgrade	2.979	3	0.395	1.000	ns	0.000	small
Opportunity to fly larger aircraft	0.302	3	0.960	1.000	ns	-0.037	small
Promotion/upgrade based on merit	2.428	3	0.488	1.000	ns	-0.008	small
Upgrade based on length of service	6.135	3	0.105	0.525	ns	0.044	small

6.4 Recognition Subfactors

Recognition Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Professional-looking uniforms	76	3	2.80	0.97	14.47
Additional vacation for long service	76	2	2.04	1.01	36.84
Recognition as a professional	76	2	1.78	0.84	44.74
Airline recognition	76	4	3.38	0.88	3.95

Recognition: Friedman Test

.y.	n	statistic	df	p	method
rank	76	73.168	3	0	Friedman test

Recognition: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Professional-looking uniforms	577	0.476	0.900	ns	0.082	small
Additional vacation for long service	345	0.023	0.093	ns	0.261	small
Recognition as a professional	601	0.300	0.900	ns	0.120	small
Airline recognition	579	0.430	0.900	ns	0.091	small

Recognition: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Professional-looking uniforms	183.0	0.120	0.360	ns	0.180	small
Additional vacation for long service	247.5	0.718	1.000	ns	0.043	small
Recognition as a professional	264.0	0.948	1.000	ns	0.009	small
Airline recognition	384.0	0.023	0.091	ns	0.264	small

Recognition: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Professional-looking uniforms	767.5	0.171	0.513	ns	0.158	small
Additional vacation for long service	496.5	0.078	0.312	ns	0.203	small
Recognition as a professional	724.0	0.385	0.770	ns	0.100	small
Airline recognition	618.0	0.694	0.770	ns	0.046	small

Recognition: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Professional-looking uniforms	119.5	0.020	0.078	ns	0.269	small
Additional vacation for long service	355.5	0.032	0.096	ns	0.247	small
Recognition as a professional	214.0	0.600	1.000	ns	0.061	small
Airline recognition	274.0	0.511	1.000	ns	0.077	small

Recognition: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Professional-looking uniforms	4.887	3	0.180	0.540	ns	0.026	small
Additional vacation for long service	8.274	3	0.041	0.163	ns	0.073	moderate
Recognition as a professional	1.184	3	0.757	1.000	ns	-0.025	small
Airline recognition	0.637	3	0.888	1.000	ns	-0.033	small

6.5 Schedule Subfactors

Schedule Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Fixed schedule	76	3.5	3.18	1.64	25.00
Variable schedule	76	3.0	3.39	1.39	14.47
Flexible work rules	76	2.0	2.12	1.31	42.11
Bid line seniority system	76	3.0	2.82	1.27	18.42
Vacation bidding rules	76	3.0	3.49	0.97	0.00

Schedule: Friedman Test

.y.	n	statistic	df	p	method
rank	76	37.632	4	0	Friedman test

Schedule: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Fixed schedule	464.5	0.472	1.00	ns	0.083	small
Variable schedule	493.5	0.724	1.00	ns	0.041	small
Flexible work rules	669.0	0.058	0.29	ns	0.218	small
Bid line seniority system	574.5	0.514	1.00	ns	0.076	small
Vacation bidding rules	479.0	0.588	1.00	ns	0.063	small

Schedule: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Fixed schedule	202.5	0.248	0.992	ns	0.134	small
Variable schedule	387.0	0.036	0.180	ns	0.243	small
Flexible work rules	229.5	0.489	0.992	ns	0.081	small
Bid line seniority system	270.5	0.972	0.992	ns	0.005	small
Vacation bidding rules	204.0	0.256	0.992	ns	0.132	small

Schedule: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Fixed schedule	606.0	0.622	1	ns	0.057	small
Variable schedule	647.0	0.977	1	ns	0.004	small
Flexible work rules	714.0	0.462	1	ns	0.085	small
Bid line seniority system	747.5	0.276	1	ns	0.126	small
Vacation bidding rules	551.5	0.263	1	ns	0.129	small

Schedule: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Fixed schedule	177.0	0.235	1	ns	0.137	small
Variable schedule	286.5	0.410	1	ns	0.096	small
Flexible work rules	227.5	0.797	1	ns	0.031	small
Bid line seniority system	216.0	0.645	1	ns	0.054	small
Vacation bidding rules	257.0	0.779	1	ns	0.033	small

Schedule: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Fixed schedule	1.454	3	0.693	1.000	ns	-0.021	small
Variable schedule	0.483	3	0.923	1.000	ns	-0.035	small
Flexible work rules	4.079	3	0.253	0.968	ns	0.015	small
Bid line seniority system	4.188	3	0.242	0.968	ns	0.016	small
Vacation bidding rules	5.826	3	0.120	0.600	ns	0.039	small

6.6 Operational Subfactors

Operational Subfactors - Descriptive Statistics

item	n	median	mean	sd	pct_rank1
Unambiguous SOPs	76	3	3.07	1.59	28.95
Proactive training environment	76	3	2.84	1.17	11.84
Well-maintained aircraft	76	2	2.25	1.16	35.53
Well-equipped aircraft	76	5	4.13	1.18	1.32
Highly skilled fellow pilots	76	3	2.71	1.24	22.37

Operational: Friedman Test

.y.	n	statistic	df	p	method
rank	76	59.463	4	0	Friedman test

Operational: Age Group Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Unambiguous SOPs	486.0	0.655	1.000	ns	0.052	small
Proactive training environment	406.0	0.145	0.725	ns	0.168	small
Well-maintained aircraft	556.0	0.671	1.000	ns	0.050	small
Well-equipped aircraft	551.5	0.692	1.000	ns	0.046	small
Highly skilled fellow pilots	608.0	0.283	1.000	ns	0.124	small

Operational: Gender Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Unambiguous SOPs	255.0	0.825	1	ns	0.027	small
Proactive training environment	240.0	0.626	1	ns	0.057	small
Well-maintained aircraft	237.0	0.586	1	ns	0.064	small
Well-equipped aircraft	328.5	0.247	1	ns	0.135	small
Highly skilled fellow pilots	290.0	0.705	1	ns	0.045	small

Operational: Position Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Unambiguous SOPs	620.0	0.740	1	ns	0.039	small
Proactive training environment	722.5	0.416	1	ns	0.094	small
Well-maintained aircraft	618.0	0.720	1	ns	0.042	small
Well-equipped aircraft	637.5	0.883	1	ns	0.018	small
Highly skilled fellow pilots	655.5	0.955	1	ns	0.007	small

Operational: Military Comparisons

item	statistic	p	p_adj_holm	p.adj.signif	effsize	magnitude
Unambiguous SOPs	287.0	0.405	1	ns	0.096	small
Proactive training environment	280.0	0.481	1	ns	0.082	small
Well-maintained aircraft	218.0	0.668	1	ns	0.050	small
Well-equipped aircraft	204.5	0.463	1	ns	0.085	small
Highly skilled fellow pilots	225.0	0.768	1	ns	0.035	small

Operational: Experience Comparisons

item	statistic	df	p	p_adj_holm	p.adj.signif	effsize	magnitude
Unambiguous SOPs	4.274	3	0.233	0.932	ns	0.018	small
Proactive training environment	0.476	3	0.924	1.000	ns	-0.035	small
Well-maintained aircraft	1.985	3	0.575	1.000	ns	-0.014	small
Well-equipped aircraft	0.326	3	0.955	1.000	ns	-0.037	small
Highly skilled fellow pilots	5.161	3	0.160	0.800	ns	0.030	small

6.7 Hierarchical FDR Screening Results

Construct-Level Screening: Benjamini-Hochberg FDR (q=0.10)

construct	n_subfactors	min_p	rank	p_adj_fdr	passes_screen	decision
Quality of Life	6	0.0147	1	0.0588	TRUE	Proceed to detailed testing
Recognition	4	0.0196	2	0.0588	TRUE	Proceed to detailed testing
Schedule	5	0.0359	3	0.0718	TRUE	Proceed to detailed testing
Professional	5	0.0493	4	0.0739	TRUE	Proceed to detailed testing
Financial	6	0.0691	5	0.0829	TRUE	Proceed to detailed testing
Operational	5	0.1450	6	0.1450	FALSE	No demographic differences detected

Screening Summary:

• Constructs passing FDR screen (p_adj < 0.10): 5 of 6

Note

For constructs passing screening, demographic comparisons have been adjusted using Holm’s procedure. Tests with p_adj_holm < 0.05 indicate significant demographic differences in subfactor prioritization.

7 Combined Results Summary

Combined Analysis Summary: Multiple Testing Approach

Analysis	Total_Tests	FDR_Method	Significant_FDR	Note
General Factors	36	BH q=0.10	2	6 factors × 5 demographics (no Position analysis)
Subfactor Analysis	155	Hierarchical: BH screening + Holm within	5	5 of 6 constructs pass screening

7.1 Summary

General Retention Factors (Part 1):

• Total demographic comparisons: 36
• Significant at FDR q=0.10: 2

Subfactor Analysis (Part 2):

• Constructs analyzed: 6
• Total subfactors: 31
• Constructs passing FDR screening: 5
• Constructs with demographic differences: Quality of Life, Recognition, Schedule, Professional, Financial

TipInterpretation

The hierarchical FDR procedure controls for the 155 subfactor tests by:

1. Screening at construct level (BH-FDR q=0.10 on 6 tests)
2. Applying Holm correction within constructs that pass screening

This approach maintains family-wise error rate control while preserving power to detect genuine demographic differences.

8 Limitations

WarningStatistical Power Considerations

With n = 76, this study has limited statistical power. Non-significant results should not be interpreted as evidence of no effect. Many analyses may be underpowered to detect small-to-medium effects.

This analysis has several important limitations:

8.1 Sample Size and Power

The total sample of n = 76 provides adequate power only for detecting large effects (Cohen’s d > 0.8 or r > 0.5). For demographic comparisons:

Comparison	Group Sizes	Detectable Effect (80% power)
Age groups	~40 vs ~36	Medium (r ≈ 0.35)
Experience	~19 per quartile	Large (eta² > 0.10)
Gender	67 vs 8	Very large only (r > 0.6)
Military	~35 vs ~40	Medium (r ≈ 0.35)
Position	~45 vs ~30	Medium (r ≈ 0.35)

Gender comparisons warrant particular caution: With only 8 female respondents, the analysis has approximately 20% power to detect medium effects - meaning 80% of true medium-sized gender differences would go undetected.

8.2 Additional Limitations

1. Multiple Testing Burden: Despite FDR control, the large number of tests (155 in subfactor analysis) increases false discovery risk; the expected number of false discoveries at q=0.10 is approximately 10% of significant findings
2. Self-Selection Bias: Survey respondents may not represent all U.S. airline pilots; those with strong opinions about retention may be overrepresented
3. Cross-Sectional Design: Retention priorities may change over career stage; this snapshot cannot capture temporal dynamics
4. Ranking Methodology: Forced rankings prevent assessment of absolute importance; factors ranked low may still be important in absolute terms

9 References

9.1 Primary Sources

Hickey, M. J. (2025). Rethinking pilot retention in the United States: An analysis of key factors [Doctoral dissertation, University of North Dakota]. ProQuest Dissertations & Theses. https://www.proquest.com/docview/3246414757

Efthymiou, M., Njoya, E. T., Lo, P. L., Papatheodorou, A., & Randall, D. (2020). The factors influencing entry level airline pilot retention: An empirical study of Ryanair. Journal of Air Transport Management, 91, 101997. https://doi.org/10.1016/j.jairtraman.2020.101997

9.2 Statistical Methods

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289-300.

Bender, R., & Lange, S. (1999). Multiple test procedures other than Bonferroni’s deserve wider use. BMJ, 318(7183), 600-601.

Armstrong, R. A. (2014). When to use the Bonferroni correction. Ophthalmic and Physiological Optics, 34(5), 502-508.

Li, J., & Ghosh, J. K. (2014). A two-step hierarchical hypothesis set testing framework. BMC Bioinformatics, 15, 108.